Imported DeepXF version:0.0.1. Example call by using:
*********************** SET MODEL/BASE CONFIGURATIONS ************************
select_model, select_user_path, select_scaler, forecast_window = Forecast.set_model_config(select_model='rnn', select_user_path='./forecast_folder_path/', select_scaler='minmax', forecast_window=1)
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model_df, orig_df = Helper.get_variable(df, ts, fc)
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hidden_dim, layer_dim, batch_size, dropout, n_epochs, learning_rate, weight_decay = Forecast.hyperparameter_config(hidden_dim=64,layer_dim = 3, batch_size=64, dropout = 0.2, n_epochs = 30, learning_rate = 1e-3, weight_decay = 1e-6)
********************** DEEP LEARNING BASED FORECASTING ***********************
opt, scaler = Forecast.train(df=df_full_features, target_col='value', split_ratio=0.2, select_model=select_model, select_scaler=select_scaler, forecast_window=forecast_window, batch_size=batch_size, hidden_dim=hidden_dim, layer_dim=layer_dim,dropout=dropout, n_epochs=n_epochs, learning_rate=learning_rate, weight_decay=weight_decay)
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forecasted_data, ff_full_features, ff_full_features_ = Forecast.forecast(model_df, ts, fc, opt, scaler, period=25, fq='h', select_scaler=select_scaler,)
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Helper.explainable_forecast(df_full_features, ff_full_features_, fc, specific_prediction_sample_to_explain=145370, input_label_index_value=0, num_labels=1)
****************** DYNAMIC FACTOR MODEL BASED NOWCASTING *********************
select_model, select_user_path, select_scaler, forecast_window = Forecast.set_model_config(select_model='em', select_user_path='./forecast_folder_path/', select_scaler='minmax', forecast_window=5)
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nowcast_full_data, nowcast_pred_data = EMModel.nowcast(df_full_features, ts, fc, period=5, fq='h', forecast_window=forecast_window, select_model=select_model)
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EMModel.explainable_nowcast(df_full_features, nowcast_pred_data, fc, specific_prediction_sample_to_explain=145370, input_label_index_value=0, num_labels=1)